As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option available to users is information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, airline reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software components that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.
Memory allocation functions are useful for allocating memory in both single and multiprocessor computer systems. By definition, multiprocessor computer systems (multiprocessor computers) contain multiple processors that can execute multiple parts of a computer program or multiple distinct programs simultaneously, in a manner known as parallel computing. In general, multiprocessor computers execute multithreaded-programs or multiple single-threaded programs faster than conventional single processor computers that must execute programs sequentially. The actual performance advantage may depend upon a number of factors, including the degree to which parts of a multithreaded-program or multiple distinct programs can be executed in parallel and the architecture of the particular multiprocessor computer at hand.
Multiprocessor computers may be classified by how they share information among the processors. Shared-memory multiprocessor computers offer a common physical memory address space that all processors can access. Multiple processes or multiple threads within the same process can communicate through shared variables in memory that allow them to read or write to the same memory location in the computer. Message passing multiprocessor computers, in contrast, have a separate memory space for each processor, requiring processes in such a system to communicate through explicit messages to each other.
Shared-memory multiprocessor computers may further be classified by how the memory is physically organized. In distributed shared-memory computers, the memory is divided into modules physically placed near each processor and I/O device. Although all of the memory modules are globally accessible, a processor or I/O device can access memory placed nearby faster than memory placed remotely. Because the memory access time differs based on memory location, distributed shared memory systems are often called non-uniform memory access (NUMA) machines. By contrast, in centralized shared-memory computers, the memory is physically in one location. Centralized shared-memory computers are called uniform memory access (UMA) machines because the memory is equidistant in time from each of the processors and I/O devices. Both forms of memory organization typically use high-speed cache memory in conjunction with main memory to reduce execution time.
Multiprocessor computers with distributed shared memory are often organized into multiple nodes with one or more processors per node. These individual nodes usually contain a processor, memory, one or more input-output devices (I/O), and an interface connection network that connects all the nodes. The interface connection network operates using a protocol. Further information on multiprocessor computer systems in general and NUMA machines in particular can be found in Computer Architecture: A Quantitative Approach (2nd Ed. 1996), by D. Patterson and J. Hennessy.
The art of designing an I/O system is finding a design that meets goals for cost and variety of devices while avoiding bottlenecks to I/O performance. This means that components must be balanced between main memory and the I/O device, because performance can only be as good as the weakest link in the I/O chain. In a NUMA information handling system the memory is physically closer to an I/O device on the same node than a I/O device on another node. Consequently, I/O devices run faster if their memory is placed on the node containing the I/O device, since the controller for the I/O device would not need to communicate between nodes. Therefore, there exists a need to provide a system that uses pre-programmed information about which memory resource is closest to a particular I/O device to direct a device driver to transmit data between the selected I/O device and the closest memory resource when needed. In a UMA machine, in contrast, the memory is substantially equidistant from all I/O devices, and there is no performance advantage to placing an I/O device's memory in any particular range of physical addresses.